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Remembering Bob Dennard, inventor of the chip that changed the world

Meet AI-Hilbert, a new algorithm for transforming scientific discovery

Teaching AI models to improve themselves 

For LLMs, IBM’s NorthPole chip overcomes the tradeoff between speed and efficiency

Accelerating discoveries with new AI tools, powerful chips — and turkey

IBM and Université de Sherbrooke announce two quantum research chairs

IBM and ESA open-source TerraMind, the best performing generative AI model for Earth observation

Eurocrypt 2025

NAACL 2025

ODSC East 2025

DAC 2025

SDM 2025

Trustworthy AI

Trustworthy Generation

Natural Language Processing

Generative AI

Exploratory Science

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Quantum Community

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Explainable AI

Technology impacts every aspect of our work and lives. It is imperative that technology is built responsibly to reduce differential effects on various populations. At IBM Research, we are working to ensure that the technologies we create promote beneficial outcomes for our clients and for the world.

Responsible Technology

IBM has been at the forefront of computer science research since the field’s inception. Our research today focuses on achieving breakthroughs in automation, information processing, and computation. Our goal is to complement and extend human performance — and advance society as a whole. 

We’re working on automation, information processing, and computation research to complement and extend human performance and advance society.

Our long history of research has had an enduring impact on computer science, operations research, and information theory. We’re currently focused on optimization, probability, complexity, geometry of data, as well as linear and multi-linear algebra, to deliver tools that are fundamental to big data and AI.

Mathematical Sciences

We’re focused on foundational mathematical research with the aim of delivering tools to that are fundamental to big data and AI.

Our physical sciences researchers seek to understand materials and their properties through advanced characterization methods, explore novel devices and materials for new computational platforms, and apply physics to improve AI algorithms and interpretability.



We’re using physics to improve AI algorithms and interpretability, as well as novel materials for new computational platforms. 


Our researchers seek to answer some of the most fundamental questions. We strive for a greater understanding of how our world works and how we can harness that knowledge to advance science, mathematics, and computation.

Darío Gil stands before a photo of Bob Dennard at the memorial event for the late IBM engineer

Mathematical constants and variables in white boxes float on a black background, connected with green arrows

IBM Research scientists are working on different approaches to teach AI models how to improve themselves

A 2U server blade containing NorthPole cards

Exploratory Science

Our work

IBM and ESA open-source TerraMind, the best performing generative AI model for Earth observation

IBM and Université de Sherbrooke announce two quantum research chairs

Accelerating discoveries with new AI tools, powerful chips — and turkey

For LLMs, IBM’s NorthPole chip overcomes the tradeoff between speed and efficiency

Teaching AI models to improve themselves

Meet AI-Hilbert, a new algorithm for transforming scientific discovery

Topics

Publications

MDLab: AI frameworks for Carbon Capture and Battery Materials

CIRCUITSYNTH-RL: LLM-Based Circuit Topology Synthesis with RL Refinement

Guardrails in generative AI workflows via orchestration

POKE: A Compact and Efficient PKE from Higher-dimensional Isogenies

Hybrid Bayesian Optimization with DIRECT

The Literary Canons of Large-Language Models: An Exploration of the Frequency of Novel and Author Generations Across Gender, Race and Ethnicity, and Nationality